The purpose of this study was to develop a single procedure for comparing population variances which could be used for distribution forms. Bootstrap methodology was used to estimate the variability of the sample variance statistic when the population distribution was normal, platykurtic and leptokurtic. The data for the study were generated and…

A review of the literature on multiple comparison procedures suggests several alternative approaches for comparing means when population variances differ. These include: (1) the approach of P. A. Games and J. F. Howell (1976); (2) C. W. Dunnett's C confidence interval (1980); and (3) Dunnett's T3 solution (1980). These procedures control the…

This study examined the sampling distribution of the analysis of variance F ratio in the two sample cases when it followed a preliminary test for variance equality. When the population variances were equal, the sampling distribution approximated the theoretical F distribution quite well, but not when population variances differed. (JAZ)

Using computer simulated data, the Type I error rate and statistical power were empirically estimated for several pairwise multiple comparison strategies for situations where population variances differ. Focus was on comparing modified Bonferroni procedures with Dunnett's solutions, and determining whether or not J. P. Shaffer's suggestion of…

The sampling distributions of five popular measures of association with and without two bias adjusting methods were examined for the single factor fixed-effects multivariate analysis of variance model. The number of groups, sample sizes, number of outcomes, and the strength of association were manipulated. The results indicate that all five…

This study considers the problem of performing all pairwise comparisons of column means for a two-by-four additive nonorthogonal factorial analysis of variance (ANOVA) model where cell variances are heterogeneous. Extensions of the following procedures are considered: (1) Games-Howell (1976) procedure; (2) the C. W. Dunnett (1980) T3 and C…

The efficacy of two improvement-over-chance or "I" effect sizes, derived from predictive discriminant analysis (PDA) and logistic regression analysis (LRA), were investigated for two-group univariate mean comparisons. Data were generated under selected levels of population separation, variance pattern, sample size, and distribution…

This study investigated the robustness of the James second-order test (James 1951; Wilcox, 1989) and the univariate F test under a two-factor fixed-effect analysis of variance (ANOVA) model in which cell variances were heterogeneous and/or distributions were nonnormal. With computer-simulated data, Type I error rates and statistical power for the…

The use of analysis of variance (ANOVA), multivariate analysis of variance (MANOVA), and analysis of covariance (ANCOVA) by educational researchers was studied through review of several prominent research journals. The analyses suggest that researchers rarely verify that validity assumptions are satisfied, and typically use analyses that are…

Studied the efficacy of two improvement-over-chance or "I" effect sizes derived from predictive discriminant analysis and logistic regression analysis for two-group univariate mean comparisons through simulation. Discusses the ways in which the usefulness of each of the indices depends on the population characteristics. (SLD)

Type I error rates and statistical power for the univariate F test and the James second-order test were estimated for the two-factor fixed-effects completely randomized design. Results reveal that the F test Type I error rate can exceed the nominal significance level when cell variances differ. (SLD)

Analysis of 19 studies using omnibus analysis of variance (ANOVA) F-tests resulted in reasons for replacing ANOVA with focused hypothesis testing, which is easy to compile and understand; is flexible; enables trend analysis, determination of confidence intervals, adjustments for violated assumptions, and control of Type 1 errors; makes effect size…

Two-stage sampling procedures for comparing two population means when variances are heterogeneous have been developed by D. G. Chapman (1950) and B. K. Ghosh (1975). Both procedures assume sampling from populations that are normally distributed. The present study reports on the effect that sampling from non-normal distributions has on Type I error…

Applied researchers frequently precede analyses of interest with one or more preliminary tests, used to help researchers determine which variables to examine more closely, or whether there are anomalies in the data set. These texts can be classified into three categories: omnibus tests, tests for model fit, and exploratory tests. Fifty-four…

Null hypothesis significance testing alone is not sufficient for program evaluation. To assess program impact adequately, effect sizes should be reported and interpreted in the context of similar or alternate programs. A popular effect size for the treatment-control group design has been the standardized mean difference, delta. Several estimators…